本文已被:浏览 783次 下载 1954次
Received:July 18, 2020 Revised:August 13, 2020
Received:July 18, 2020 Revised:August 13, 2020
中文摘要: 由于车联网中的节点多为快速移动的车辆, 因此节点的移动性使得车联网网络拓扑的结构变得更加复杂, 节点的分布范围变得更加广泛, 恶意节点对路由的潜在威胁也逐渐增加. 这些不确定因素都使车载节点间通讯的安全性与节点的空间信任值受到了的影响. 本文主要研究的内容是构建出一种基于反馈节点信任度的信任评估模型, 与经典的机会路由模型相结合, 提出一个优于现有、且更适合目前车联网复杂多变的环境所需要的可信路由模型, 进而提高节点间通信的安全性与准确性. 仿真实验结果表明: 各个路由模型的性能在不同预设值下差异明显. 其中FB-SF模型在提高数据传输准确度的同时尽可能的提高了恶意节点检测比.
Abstract:Because the nodes in VANET are mostly fast-moving vehicles, the mobility of the nodes makes the VANET topology more complicated, the distribution range of the nodes wider, and the potential threat of malicious nodes to the routing gradually greater. These uncertain factors have affected the communication security and space trust values of the vehicle-mounted nodes. In this study, we mainly build a trust evaluation model based on the trust degree of feedback nodes and combine it with the classical opportunistic routing model to propose a trusted routing model better than the existing ones and more suitable for the current complex environment of the VANET. Thus, the security and accuracy of communication between the nodes are further improved. The simulation results show that the performance of each routing model differs significantly under different preset values. Specifically, the FB-SF model increases the detection ratio of malicious nodes as much as possible while improving the accuracy of data transmission.
文章编号: 中图分类号: 文献标志码:
基金项目:陕西省基金重点项目(2019GY-062)
Author Name | Affiliation | |
ZHANG Yao | School of Information Engineering, Chang’an University, Xi’an 710064, China | 18829899353@163.com |
Author Name | Affiliation | |
ZHANG Yao | School of Information Engineering, Chang’an University, Xi’an 710064, China | 18829899353@163.com |
引用文本:
张瑶.车联网环境下基于机会网络的可信路由模型.计算机系统应用,2021,30(3):214-220
ZHANG Yao.Trusted Routing Model Based on Opportunistic Networks in VANET.COMPUTER SYSTEMS APPLICATIONS,2021,30(3):214-220
张瑶.车联网环境下基于机会网络的可信路由模型.计算机系统应用,2021,30(3):214-220
ZHANG Yao.Trusted Routing Model Based on Opportunistic Networks in VANET.COMPUTER SYSTEMS APPLICATIONS,2021,30(3):214-220